Topic model for graph mining based on hierarchical Dirichlet process
In this paper, a nonparametric Bayesian graph topic model (GTM) based on hierarchical Dirichlet process (HDP) is proposed. The HDP makes the number of topics selected flexibly, which breaks the limitation that the number of topics need to be given in advance. Moreover, the GTM releases the assumptio...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2020-01-01
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| Series: | Statistical Theory and Related Fields |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/24754269.2019.1593098 |